[GitHub] [spark] MaxGekk commented on a change in pull request #26189: [SPARK-29533][SQL][TEST] Benchmark casting strings to intervals

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MaxGekk commented on a change in pull request #26189: [SPARK-29533][SQL][TEST] Benchmark casting strings to intervals
URL: https://github.com/apache/spark/pull/26189#discussion_r337046377
 
 

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 File path: sql/core/src/test/scala/org/apache/spark/sql/execution/benchmark/IntervalBenchmark.scala
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+/*
+ * Licensed to the Apache Software Foundation (ASF) under one or more
+ * contributor license agreements.  See the NOTICE file distributed with
+ * this work for additional information regarding copyright ownership.
+ * The ASF licenses this file to You under the Apache License, Version 2.0
+ * (the "License"); you may not use this file except in compliance with
+ * the License.  You may obtain a copy of the License at
+ *
+ *    http://www.apache.org/licenses/LICENSE-2.0
+ *
+ * Unless required by applicable law or agreed to in writing, software
+ * distributed under the License is distributed on an "AS IS" BASIS,
+ * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+ * See the License for the specific language governing permissions and
+ * limitations under the License.
+ */
+
+package org.apache.spark.sql.execution.benchmark
+
+import scala.collection.mutable.ListBuffer
+
+import org.apache.spark.benchmark.Benchmark
+import org.apache.spark.sql.SaveMode.Overwrite
+import org.apache.spark.sql.internal.SQLConf
+
+/**
+ * Synthetic benchmark for interval functions.
+ * To run this benchmark:
+ * {{{
+ *   1. without sbt:
+ *      bin/spark-submit --class <this class> --jars <spark core test jar> <sql core test jar>
+ *   2. build/sbt "sql/test:runMain <this class>"
+ *   3. generate result:
+ *      SPARK_GENERATE_BENCHMARK_FILES=1 build/sbt "sql/test:runMain <this class>"
+ *      Results will be written to "benchmarks/IntervalBenchmark-results.txt".
+ * }}}
+ */
+object IntervalBenchmark extends SqlBasedBenchmark {
+
+  private def doBenchmark(cardinality: Long, exprs: String*): Unit = {
+    withSQLConf(SQLConf.WHOLESTAGE_CODEGEN_ENABLED.key -> "true") {
+      spark
+        .range(0, cardinality, 1, 1)
+        .selectExpr(exprs: _*)
+        .write
+        .format("noop")
+        .mode(Overwrite)
+        .save()
+    }
+  }
+
+  private def addCase(
+      benchmark: Benchmark,
+      cardinality: Long,
+      name: String,
+      exprs: String*): Unit = {
+    benchmark.addCase(name, numIters = 3) { _ =>
+      doBenchmark(cardinality, exprs: _*)
+    }
+  }
+
+  private def buildString(withPrefix: Boolean, units: Seq[String] = Seq.empty): String = {
+    val sep = if (units.length > 0) ", " else ""
+    val otherUnits = sep + s"'${units.mkString(" ")}'"
+    val prefix = if (withPrefix) "'interval'" else "''"
+    s"concat_ws(' ', ${prefix}, cast(id % 10000 AS string), 'years'${otherUnits})"
 
 Review comment:
   Overhead of preparing benchmark input is non-zero in most cases. That's why I always measure the input preparation, see the first lines in the results: https://github.com/apache/spark/pull/26189/files#diff-586487fac2b9b1303aaf80adf8fa37abR5-R6 . So, we can subtract time for preparation from other numbers.
   
   > I think we should construct the string manually and only benchmark string literal to interval.
   
   Could you explain, please, what do you mean by "manually". And how this will make the overhead for preparation insignificant.

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